System and method to detect proper seatbelt usage and distance

ABSTRACT

A system and method for detecting seatbelt positioning includes capturing, by a camera, a near infrared (NIR) image of an occupant, applying a median filter to the NIR image to remove glints; converting the NIR image to a black-and-white image, scanning across the black-and-white (B/W) image to detect a plurality of transitions between black and white segments corresponding to stripes extending lengthwise along a length of the seatbelt, and using detections of the plurality of transitions to indicate a detection of the seatbelt. Converting the NIR image to the black-and-white image may include using a localized binary threshold to determine whether a given pixel in the B/W image should be black or white based on whether a corresponding source pixel within the NIR image is brighter than an average of nearby pixels within a predetermined distance of the corresponding source pixel.

BACKGROUND 1. Field of the Invention

The present invention generally relates systems and methods fordetecting proper seatbelt usage and distance to an occupant using avision system, such as an near-infrared (NIR) camera.

2. Description of Related Art

Cameras and other image detection devices have been utilized to detectone or more objects. Control systems that are in communication withthese cameras can receive images captured by the cameras and processthese images. The processing of these images can include detecting oneor more objects found in the captured images. Based on these detectedobjects, the control system may perform some type of action in responseto these detected variables.

Conventional systems for detecting seatbelt usage typically rely upon aseat belt buckle switch. However, those conventional systems are unableto detect if the seatbelt is properly positioned or if the seat beltbuckle is being spoofed. Seat track sensors are typically used todetermine distance to an occupant of a motor vehicle. However, such useof seat track sensors do not account for body position of the occupantrelative to the seat.

SUMMARY

In one example, a method for detecting seatbelt positioning includescapturing, by a camera, a near infrared (NIR) image of an occupant. Themethod also includes converting the NIR image to a black-and-whiteimage; and scanning across the black-and-white image to detect aplurality of transitions between black and white segments correspondingto stripes extending lengthwise along a length of the seatbelt, andusing detections of the plurality of transitions to indicate a detectionof the seatbelt.

In another example, a system for detecting seatbelt positioning,comprises a seatbelt having a plurality of stripes extending lengthwisealong a length thereof, the plurality of stripes being arranged in analternating pattern of bright and dark in near-infrared. The system alsocomprises a camera configured to capture a near infrared (NIR) image ofan occupant wearing the seatbelt; and a processor in communication withthe camera and programmed to receive the NIR image of the occupantwearing the seatbelt and to determine a position of the seatbelt basedon detecting transitions corresponding to the alternating pattern of thestripes.

Further objects, features, and advantages of this invention will becomereadily apparent to persons skilled in the art after a review of thefollowing description, with reference to the drawings and claims thatare appended to and form a part of this specification.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a vehicle having a system for detecting properseatbelt usage and for detecting distance to the seatbelt;

FIG. 2 illustrates a forward looking view of a cabin of the vehiclehaving a system for detecting proper seatbelt usage and for detectingdistance to the seatbelt;

FIG. 3 illustrates a block diagram of the system for detecting properseatbelt usage and for detecting distance to the seatbelt;

FIG. 4 illustrates a first example of improper seatbelt positioning;

FIG. 5 illustrates a second example of improper seatbelt positioning;

FIG. 6 illustrates a third example of improper seatbelt positioning;

FIG. 7A shows a near infrared (NIR) image of a person wearing a seatbeltin accordance with an aspect of the present disclosure;

FIG. 7B shows a filtered image based on the NIR image of FIG. 7A, inaccordance with the present disclosure;

FIG. 7C shows a Black/White image based on the NIR image of FIG. 7A, inaccordance with the present disclosure;

FIG. 7D shows an image based on the NIR image of FIG. 7A, illustratingdetection points, in accordance with the present disclosure;

FIG. 8A shows an enlarged section of an NIR image;

FIG. 8B shows a filtered image of the enlarged section of FIG. 8A;

FIG. 9 shows a close-up NIR image of a seatbelt with an asymmetricstripe pattern, in accordance with the present disclosure;

FIG. 10 shows an enlarged section of the Black/White image of FIG. 7C,including the seatbelt and showing horizontal scanning lines, inaccordance with the present disclosure;

FIG. 11 shows an enlarged section of the image of FIG. 7D, showing adetected angle of the seatbelt, in accordance with the presentdisclosure; and

FIG. 12 shows a flowchart listing steps in a method of detectingseatbelt positioning.

DETAILED DESCRIPTION

Referring to FIG. 1 , illustrated is a vehicle 10 having a seatbeltdetection system 12 for detecting proper seatbelt usage and/or fordetecting distance to the seatbelt. In this example, the seatbeltdetection system 12 has been incorporated within the vehicle 10.However, it should be understood that the seatbelt detection system 12could be a standalone system separate from the vehicle 10. In someembodiments, the seatbelt detection system 12 may employ some or allcomponents existing in the vehicle 10 for other systems and/or for otherpurposes, such as for driver monitoring in an advanced driver assistancesystem (ADAS). Thus, the seatbelt detection system 12 of the presentdisclosure may be implemented with very low additional costs.

As to the vehicle 10, the vehicle 10 is shown in FIG. 1 as a sedan typeautomobile. However, it should be understood that the vehicle 10 may beany type of vehicle capable of transporting persons or goods from onelocation to another. As such, the vehicle 10 could, in addition to beinga sedan type automobile, could be a light truck, heavy-duty truck,tractor-trailer, tractor, mining vehicle, and the like. Also, it shouldbe understood that the vehicle 10 is not limited to wheeled vehicles butcould also include non-wheeled vehicles, such as aircraft andwatercraft. Again, the term vehicle should be broadly understood toinclude any type of vehicle capable of transporting persons or goodsfrom one location to another and it should not be limited to thespecifically enumerated examples above.

Referring to FIG. 2 , a cabin 14 of the vehicle 10 is shown. As it iswell understood in the art, the cabin 14 is essentially the interior ofthe vehicle 10 wherein occupants and/or goods are located when thevehicle is in motion. The cabin 14 of the vehicle may be defined by oneor more pillars that structurally define the cabin 14. For example, inFIG. 2 , A-pillars 16A and B-pillars 16B are shown. FIG. 1 furtherillustrates that there may be a third pillar or a C-pillar 16C. Ofcourse, it should be understood that the vehicle 10 may contain any oneof a number of pillars so as to define the cabin 14. Additionally, itshould be understood that the vehicle 10 may be engineered so as toremove these pillars, essentially creating an open-air cabin 14 such ascommonly found in automobiles with convertible tops.

Located within the cabin 14 are seats 18A and 18B. The seats 18A and 18Bare such that they are configured so as to support an occupant of thevehicle 10. The vehicle 10 may have any number of seats. Furthermore, itshould be understood that the vehicle 10 may not have any seats at all.

The vehicle 10 may have one or more cameras 20A-20F located and mountedto the vehicle 10 so as to be able to have a field a view of at least aportion of the cabin 14 that function as part of a vision system. Assuch, the cameras 20A-20F may have a field of view of the occupantsseated in the seats 18A and/or 18B. Here, cameras 20A and 20C arelocated on the A-pillars 16A. Camera 20B is located on a rearview mirror22. Camera 20D may be located on a dashboard 24 of the vehicle 10.Camera 20E and 20F may focus on the driver and/or occupant and may belocated adjacent to the vehicle cluster 21 or a steering wheel 23,respectively. Of course, it should be understood that any one of anumber of different cameras may be utilized. As such, it should beunderstood that only one camera may be utilized or numerous cameras maybe utilized. Furthermore, the cameras 20A-20F may be located and mountedto the vehicle 10 anywhere so long as to have a view of at least aportion of the cabin 14.

The cameras 20A-20F may be any type of camera capable of capturingvisual information. This visual information may be information withinthe visible spectrum, but could also be information outside of thevisible spectrum, such as infrared or ultraviolet light. Here, thecameras 20A-20F are near infrared (NIR) cameras capable of capturingimages generated by the reflection of near infrared light. Near infraredlight may include any light in the near-infrared region of theelectromagnetic spectrum (from 780 nm to 2500 nm). However, the seatbeltdetection system 12 of the present disclosure may be configured to use aspecific wavelength or range of wavelengths within the near-infraredregion.

The source of this near-infrared light could be a natural source, suchas the sun, but could also be an artificial source such as anear-infrared light source 26. The near-infrared light source 26 may bemounted anywhere within the cabin 14 of the vehicle 10 so as long as tobe able to project near-infrared light into at least a portion of thecabin 14. Here, the near-infrared light source 26 is mounted to therearview mirror 22 but should be understood that the near-infrared lightsource 26 may be mounted anywhere within the cabin 14. Additionally, itshould be understood that while only one near-infrared light source 26is shown, there may be more than one near-infrared light source 26located within the cabin 14 of the vehicle 10.

Also located within the cabin 14 may be an output device 28 for relayinginformation to one or more occupants located within the cabin 14. Here,the output device 28 is shown in a display device so as to convey visualinformation to one or more occupants located within the cabin 14.However, it should be understood that the output device 28 could be anyoutput device capable of providing information to one or more occupantslocated within the cabin 14. As such, for example, the output device maybe an audio output device that provides audio information to one or moreoccupants located within the cabin 14 of a vehicle 10. Additionally,should be understood that the output device 28 could be a vehiclesubsystem that controls the functionality of the vehicle.

Referring to FIG. 3 , a more detailed illustration of the seatbeltdetection system 12 is shown. Here, the system 12 includes a controlsystem 13 having a processor 30 in communication with a memory 32 thatcontains instructions 34 for executing any one of a number of differentmethods disclosed in this specification. The processor 30 may include asingle stand-alone processor or it may include two or more processors,which may be distributed across multiple systems working together. Thememory 32 may be any type of memory capable of storing digitalinformation. For example, the memory may be solid-state memory, magneticmemory, optical memory, and the like. Additionally, it should beunderstood that the memory 32 may be incorporated within the processor30 or may be separate from the processor 30 as shown.

The processor 30 may also be in communication with a camera 20. Thecamera 20 may be the same as cameras 20A-20F shown and described in FIG.2 . The camera 20, like the cameras 20A-20F in FIG. 2 , may be anear-infrared camera. The camera 20 may include multiple physicaldevices, such as cameras 20A-20F illustrated in FIG. 2 . The camera 20has a field of view 21.

The near-infrared light source 26 may also be in communication with theprocessor 30. When activated by the processor 30, the near-infraredlight source 26 projects near-infrared light 36 to an object 38 whichmay either absorb or reflect near-infrared light 40 towards the camera20 wherein the camera can capture images illustrating the absorbed orreflected near-infrared light 40. These images may then be provided tothe processor 30.

The processor 30 may also be in communication with the output device 28.The output device 28 may include a visual and/or audible output devicecapable of providing information to one or more occupants located withinthe cabin 14 of FIG. 2 . Additionally, it should be understood that theoutput device 28 could be a vehicle system, such as a safety system thatmay take certain actions based on input received from the processor 30.For example, the processor 30 may instruct the output device 28 to limitor minimize the functions of the vehicle 10 of FIG. 1 . As will beexplained later in this specification, one of the functions that theseatbelt detection system 12 may perform is detecting if an occupant isproperly wearing a safety belt. If the safety belt is not properly worn,the processor 30 could instruct the output device 28 to limit thefunctionality of the vehicle 10, such that the vehicle 10 can onlytravel at a greatly reduced speed.

FIG. 4 illustrates a first example of improper seatbelt positioning,showing a seatbelt 50 that is ill-adjusted on an occupant 44 sitting ona seat 18A of the vehicle 10. The ill-adjusted seatbelt 50 in thisexample, drapes loosely over the shoulder of the occupant 44. FIG. 5illustrates a second example of improper seatbelt positioning, showingthe seatbelt 50 passing under the armpit of the occupant 44. FIG. 6illustrates a third example of improper seatbelt positioning, showingthe seatbelt 50 passing behind the back of the occupant 44. The seatbeltdetection system may detect other examples of improper seatbeltpositioning, such as a seatbelt that is missing or which is not worn bythe occupant 44, even in cases where the buckle is spoofed (e.g. byplugging-in the buckle with the seatbelt behind the occupant 44 or byplacing a foreign object into the buckle latch).

FIG. 7A shows a near infrared (NIR) image of an occupant 44 wearing aseatbelt 50 in accordance with an aspect of the present disclosure. Thismay represent an image captured by the camera 20 and received by theprocessor 30. In some embodiments, the occupant 44 may be a driver ofthe vehicle 10. However, the occupant 44 could also be a passenger inthe vehicle 10. FIG. 7B shows a filtered image based on the NIR image ofFIG. 7A; FIG. 7C shows a Black/White image based on the NIR image ofFIG. 7A; and FIG. 7D shows an image based on the NIR image of FIG. 7A,illustrating detection points, in accordance with the presentdisclosure. Specifically, FIG. 7D shows the seatbelt 50 passing througheach of a first region of interest (ROI) 60 and a second ROI 62. Thefirst ROI 60 may be located above a shoulder of the occupant 44, and thesecond ROI 62 may be located below and to the left of the first ROI. Thesecond ROI 62 may correspond to a central region of the occupant's 44torso. The ROIs 60, 62 may each have a fixed location within the fieldof view 21 of the camera 20. Alternatively, the system 12 may adjust thepositions of one or both of the ROIs 60, 62 based on a detected locationof the occupant 44 within the field of view 21 of the camera 20.

FIG. 8A shows an enlarged section of an NIR image, including a part ofan occupant 44, and FIG. 8B shows a filtered image of the enlargedsection of FIG. 8A. FIGS. 8A-8B illustrate removal of glints, whichappear as small bright regions of the NIR image. The glints in thisexample are on an earring worn by the occupant 44. However, the glintsmay come from other sources, such as a frayed thread or a piece of lintor other material. The presence of glints on or near the seatbelt 50could otherwise interfere with subsequent processing steps, and couldreduce effectiveness of the proper operation of the seatbelt detectionsystem 12

FIG. 9 shows a close-up NIR image of a sealtelt 50 with an asymmetricstripe pattern, in accordance with the present disclosure. Specifically,the seatbelt 50 includes a plurality of stripes 68 a-68 g extendinglengthwise along a length of the seatbelt 50. The stripes 68 a-68 g havealternating high and low brightness in the NIR image. The illustratedseatbelt 50 includes seven (7) stripes 68 a-68 g. However, the seatbelt50 may have fewer or a greater number of the stripes 68 a-68 g. Thestripes 68 a-68 g are arranged in an asymmetric pattern, with each ofthe stripes 68 a-68 g having a corresponding width W_(a)-W_(g) in adirection perpendicular to the lengthwise dimension of the seatbelt 50.The widths W_(a)-W_(g) of the stripes 68 a-68 g sum to a total width Wtof the seatbelt 50. The stripes 68 a-68 g include two outermost stripes68 a, 68 g surrounding a plurality of interior stripes 68 b-68 f, whichtogether define a total interior width W_(ti). The widths W_(a)-W_(g) ofthe stripes 68 a-68 g may have an irregular pattern, which may reducethe changes of the system 12 having a false-positive detection. Morespecifically, the widths W_(b)-W_(f) of the interior stripes 68 b-68 fmay have an irregular pattern to reduce the chances of a false-positivedetection. A false-positive detection may be any detection of a patternmatching the pattern on the seatbelt 50 resulting from the camera 20imaging something other than the seatbelt 50.

The stripes 68 a-68 g may be a feature of the material that is woven orotherwise constructed to form the seatbelt 50. The material forming thestripes 68 a-68 g may extend through the entirety of the seatbelt 50, sothe stripes 68 a-68 g are visible on either of two opposite sides of theseatbelt 50. The stripes 68 a-68 g include an asymmetric pattern, so theorientation of the seatbelt 50 can be determined based on an image ofthe pattern of the stripes 68 a-68 g. One or more twists in the seatbelt50 can be detected as reversals of the asymmetric pattern of the stripes68 a-68 g.

FIG. 10 shows an enlarged section of the Black/White image of FIG. 7C,including the seatbelt 50 and showing horizontal scanning lines, inaccordance with the present disclosure. FIG. 10 illustrates how thesystem 12 scans across rows of pixels (the horizontal lines) and looksfor a series of seven consecutive segments with alternating colors,corresponding to the stripes 68 a-68 g, and separated by six transitionpoints. The two outermost stripes 68 a, 68 g can have any width greaterthan 0 pixels. In other words, the can have any width that is resolvableby the camera 20. The outermost stripes 68 a, 68 g may function todefine an outer edge of the next-adjacent stripes 68 b, 68 f. Theseatbelt 50 may, therefore, include five interior stripes 68 b-68 fsurrounded by the two outermost stripes 68 a, 68 f. The system 12 mayrecognize the seatbelt 50 based on the relative widths of the interiorstripes 68 b-68 f. Specifically, the interior stripes 68 b-68 f may havecorresponding widths W_(b)-W_(f) that vary from one-another to define apattern of different width ratios. Each row of pixels shown on FIG. 10may detect the seatbelt based on the pattern indicated at the bottom ofthe image. Specifically, the system 12 may detect a series of one ormore black pixels (b>0) followed by a series of white pixels having ascaled width of 1-unit (w1). Continuing left-to-right, the system 12 mayfurther detect black stripe 68 c having a scaled width of 1-unit (b1),then white stripe 68 d having a scaled width of 4-units (w4), then blackstripe 68 e having a scaled width of 2-units (b2), then white stripe 68f having a scaled width of 1-unit (w1), and finally another series ofone or more black pixels (b>0).

The ratio of widths of the interior stripes 68 b-68 f shown on FIG. 10is 1:1:4:2:1; however, the interior stripes interior stripes 68 b-68 fmay have different widths to define a different ratio. If the detectedinterior stripes 68 b-68 f match the ratio of 1:1:4:2:1, within acertain error tolerance, then a horizontal position of the seatbelt 50within each given scan line may be noted as a detection point. In someembodiments, the accumulated width of the ratio sections of thedetection event may be stored together with the detection point. Thus,the system 12 may filter out noise in a given scan line that mayotherwise match the ratio of 1:1:4:2:1, but which does not have a totalinterior width W_(ti) that is within a tolerance of the total interiorwidth W_(ti) of the seatbelt 50, as detected in scan lines that areadjacent or near the given scan line. Using the relative ratios of thewidths W_(b)-W_(f) of the corresponding interior stripes 68 b-68 fallows the system 12 to detect the seatbelt 50.

FIG. 11 shows an enlarged section of the image of FIG. 7D, showing adetected angle 70 of the seatbelt 50. Specifically, FIG. 11 shows howthe system 12 recognizes the seatbelt 50 and records its position asdetection points 64. Once multiple detection points 64 are accumulated,the angle 70 of the seatbelt 50 can be determined. The angle 70 mayrepresent a tilt of the seatbelt 50 in a longitudinal direction, or adifference in distance from the camera between a higher portion of theseatbelt 50 and a lower portion of the seatbelt 50. A detection point 64within the first ROI 60, above a shoulder of the occupant 44 representthe higher portion of the seatbelt 50. Similarly, a detection point 64within the second ROI 62, at the central region of the occupant's 44torso, may represent the lower portion of the seatbelt 50.

Once the angle 70 is determined, the actual widths of the seatbelt 50 atthe detection points 64 can be used to determine a compensated pixelwidth. For example, with an angle of 73 degrees, a detection point 64having a pixel width of 100 pixels, as measured by the camera 20,multiplied by the sine of the angle 70 (sin 73 deg.) results in acompensated pixel width of about 95.6 pixels. With a known totalinterior width W_(ti) of the seatbelt 50, and with details of the camera20 (e.g. arc-length of pixels), the location of the detection point 64on the seatbelt 50 can be determined. This distance can provide moreaccurate measurements regarding the position of the occupant 44 asopposed to conventional methods, such as those that rely upon positionof the seat.

A method 100 of detecting seatbelt positioning is shown in the flowchart of FIG. 12 . The method 100 includes capturing an image of theoccupant 44 by a camera 20 at step 102. Step 102 may include capturingthe image in the near infrared (NIR) spectrum, which may includedetecting reflected NIR light provided by a near-infrared light source26. Step 102 may further include transmitting the image, as a videostream or as one or more still images, from the camera 20 to a controlsystem 13 having a processor 30 for additional processing.

The method 100 also includes filtering the image to remove glints atstep 104. The processor 30 may perform step 104, which may includeapplying a median filter to the image. A median filter may preserveedges while smoothing abnormally bright or dark areas (i.e. glints),which may result from sealtbelt yarns, bad pixels in the camera 20, orother noise-inducing particles, such as lint stuck to the seatbelt 50.This step 104 reduces the number of false detections of black/whitetransitions, and thereby improves the performance and reliability of themethod 100.

The method 100 also includes converting the filtered image toblack-and-white (B/W) at step 106. The terms black and white may includeany representations of pixels in one of two binary states representingdark or light. The processor 30 may perform step 106, which may includeusing a localized binary threshold to determine whether any given pixelin the B/W image should be black or white. Such a localized binarythreshold may compare a source pixel in the source image (i.e. thefiltered image) to nearby pixels within a predetermined distance of thepixel. If the source pixel is brighter than an average of the nearbypixels, the corresponding pixel in the B/W image may be set to white,and if the source pixel is less bright than the average of the nearbypixels, then the corresponding pixel in the B/W image may be set toblack. In some embodiments, the predetermined distance may be about 100pixels. In some embodiments, the predetermined distance may be equal toor approximately equal to a pixel width of the seatbelt 50 with theseatbelt 50 at a nominal position relative to the camera (e.g. in use onan occupant 44 having a medium build and sitting in the seat 18 a in anintermediate position.

The method 100 also includes scanning across the B/W image to detectBlack/White (or White/Black) transitions and to use detections of thosetransitions to indicate detections 64 of the seat belt 50 at step 108.The processor 30 may perform step 108, which may include comparing therelative distances between the transitions to determine if thoserelative distances correlate to a ratio of the widths of interiorstripes 68 b-68 f of the seatbelt 50, and where they do, marking thatlocation as a detection 64. For example, the processor 30 may beprogrammed to scan across horizontal lines in the B/W image to detectgroupings of transitions spaced apart by distances that match the1:1:4:2:1 ratio of widths of the interior stripes 68 b-68 f shown onFIG. 10 . Similarly, the processor 30 may be programmed to detect areversed ratio of widths of the interior stripes 68 b-68 f (i.e.transitions separated by distances that match a 1:2:4:1:1 pattern) todetect the seatbelt 50 at a particular location and with a reversedorientation.

The method 100 also includes calculating an angle of the seatbelt 50 atstep 110. The processor 30 may perform step 110, which may include usingmultiple detection points 64, such as the positions of the seatbelt 50in two regions of interest (ROIs) 60, 62 to determine an angle 70 of theseatbelt 50. The angle 70 may represent a tilt of the seatbelt 50 in alongitudinal direction, or a difference in distance from the camerabetween a higher portion of the seatbelt 50 and a lower portion of theseatbelt 50.

The method 100 also includes calculating a distance to the seatbelt 50at step 112. The processor 30 may perform step 112, which may includeusing a pixel width of the seatbelt 50 in the ROIs 60, 62. Step 112 mayfurther use the angle of the seatbelt 50, as determined previously, tocalculate the distance to the seatbelt 50, such as the distance to the50 in one or more of the ROIs 60, 62. For example, with an angle of 73degrees, the processor 30 may determine a pixel width of a detectionpoint 64 to be 100 pixels. The processor 30 may then multiply that pixelwidth of 100 pixels times by the sine of the angle 70 (sin 73 deg.) todetermine compensated pixel width of about 95.6 pixels. With a knowntotal interior width W_(ti) of the seatbelt 50, and with details of thecamera 20 (e.g. arc-length of pixels), the processor 30 can calculatethe distance between the camera and the detection point 64 of theseatbelt 50. This distance can provide more accurate measurementsregarding the position of the occupant 44 as opposed to conventionalmethods, such as those that rely upon position of the seat.

The method 100 also includes determining if the seatbelt 50 is properlypositioned at step 114. The processor 30 may perform step 114, which mayinclude using the angle of the seatbelt 50 and/or the distance to theseatbelt 50. For example, the processor 30 may compute a measured angleof the seatbelt 50 and compare that measured angle to a range ofmeasured values that correspond to proper position of the seatbelt 50.Similarly, the processor 30 may compute one or more distances to theseatbelt 50 and those one or more distances to distances that correspondto a proper positioning of the seatbelt 50. In some embodiments, theprocessor 30 may compute a rate of change of the distances to determineif the seatbelt 50 is loose as shown, for example, on FIG. 4 . Theprocessor 30 may also designate the seatbelt 50 as being improperlypositioned if the processor 30 is unable to identify the seatbelt 50 inone or more regions of the image, such as in one or more of the ROIs 60,62. Examples of such improper positioning are shown in FIGS. 5 and 6 .

The method 100 also includes determining if the seatbelt 50 is twistedat step 116. The processor 30 may perform step 116, which may includedetecting one or more reversals of an asymmetric pattern on theseatbelt. For example, the processor 30 may designate the seatbelt asbeing improperly positioned if it detects a number of twists in theseatbelt 50 that exceeds a threshold value for twists.

The method 100 also includes generating a first signal if the system 12determines that the seatbelt 50 is properly positioned or generating asecond signal if the system 12 determines that the seatbelt 50 isimproperly positioned at step 118. The processor 30 may perform step118, which may include providing an enunciation to the occupant 44, suchas a sound or display of a warning message. In another example, theprocessor 30 may signal an output device 28, such as a safety system, totake actions to limit or minimize the functions of the vehicle 10. Forexample, the vehicle 10 may be prevented from moving or from exceeding avery low speed until and unless the system 12 determines that theseatbelt 50 is properly positioned.

By executing the method of the present disclosure, the seatbeltdetection system 12 can determine if the occupant 44 is properly wearingtheir seatbelt 50. The system and method of the present disclosure canimprove the confidence that the occupant 44 is properly wearing theseatbelt 50.

In addition, as stated previously, the seatbelt 50 may have lightabsorbing and/or reflecting material 50C located on or disposed on theseatbelt 50. The cameras 20A-20F can capture images of the material 50C.As stated before, this material 50C may be in a known pattern havingpattern elements that are separated from each other by known distances52. The seatbelt detection system 12 can then review these capturedimages from the camera 20A-20F and determine if the distance of theseatbelt 50 to the camera is generally an expected distance indicatingthat the seatbelt 50 is properly across the body 48 of the occupant 44.In addition, because this pattern is known, clothing that the occupant44 may be wearing that may reflect and/or absorb light, such as infraredlight, can be ignored as it is highly unlikely that the clothing worn bythe occupant would have a pattern matching that of the pattern of thestripes 68 a-68 g on the seatbelt 50.

If a determination is made that the occupant 44 is properly wearing theseatbelt 50, the seatbelt detection system 12 can allow the vehicle 10to operate in a normal mode. However, if the seatbelt detection system12 indicates that the occupant 44 is not properly wearing the seatbelt50, the control system 12 could take any one of a number of differentactions. For example, the seatbelt detection system 12 could indicate tothe occupant 44 using the output device 28 so as to provide a visualand/or audible cue that the seatbelt 50 is not being properly worn.Additionally, the output device 28 could be in communication with anyone of a number of different vehicle systems so as to restrict theoperation of the vehicle 10 until the seatbelt 50 is being properly wornby the occupant 44.

The seatbelt detection system 12 may also be in communication with othercontrol systems so as to improve the reliability of the system. Forexample, the seatbelt detection system 12 may also be in communicationwith one or more sensors, such as the sensors that detect the safetybelt latch 61 or tongue is inserted into the safety belt buckle 63. Ifthe seatbelt detection system 12 determines that the safety belt buckleis properly latched and determines that the seatbelt 50 is properlypositioned across the body 48 of the occupant 44, the seatbelt detectionsystem 12 can, with more confidence, determine that the seatbelt 50 isbeing properly utilized by the occupant 44.

In some embodiments, dedicated hardware implementations, such asapplication specific integrated circuits, programmable logic arrays, andother hardware devices, can be constructed to implement one or moresteps of the methods described herein. Applications that may include theapparatus and systems of various embodiments can broadly include avariety of electronic and computer systems. One or more embodimentsdescribed herein may implement functions using two or more specificinterconnected hardware modules or devices with related control and datasignals that can be communicated between and through the modules, or asportions of an application-specific integrated circuit. Accordingly, thepresent system encompasses software, firmware, and hardwareimplementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

Further, the methods described herein may be embodied in acomputer-readable medium. The term “computer-readable medium” includes asingle medium or multiple media, such as a centralized or distributeddatabase, and/or associated caches and servers that store one or moresets of instructions. The term “computer-readable medium” shall alsoinclude any medium that is capable of storing, encoding or carrying aset of instructions for execution by a processor or that cause acomputer system to perform any one or more of the methods or operationsdisclosed herein.

As a person skilled in the art will readily appreciate, the abovedescription is meant as an illustration of the principles of thisinvention. This description is not intended to limit the scope orapplication of this invention in that the invention is susceptible tomodification, variation, and change, without departing from the spiritof this invention, as defined in the following claims.

1. A method for detecting seatbelt positioning, comprising: capturing,by a camera, a near infrared (NIR) image of an occupant; converting theNIR image to a black-and-white image; scanning across theblack-and-white image to detect a plurality of transitions between blackand white segments corresponding to stripes extending lengthwise along alength of the seatbelt, and using detections of the plurality oftransitions to indicate a detection of the seatbelt.
 2. The method ofclaim 1, further comprising applying a median filter to the NIR image toremove glints prior to converting the NIR image to the black-and-whiteimage.
 3. The method of claim 1, wherein converting the NIR image to theblack-and-white image includes using a localized binary threshold todetermine whether a given pixel in the black-and-white image should beblack or white based on whether a corresponding source pixel within theNIR image is brighter than an average of nearby pixels within apredetermined distance of the corresponding source pixel.
 4. The methodof claim 3, wherein the predetermined distance is about 100 pixels orwherein the predetermined distance is approximately equal to a pixelwidth of the seatbelt.
 5. The method of claim 1, wherein using thedetections of the plurality of transitions to indicate a detection ofthe seatbelt further comprises comparing relative distances between thetransitions to a ratio of the widths of the stripes.
 6. The method ofclaim 1, wherein the widths of the stripes define an asymmetric pattern.7. The method of claim 6, further comprising: determining an orientationof the seatbelt based on an order of the plurality of transitionscorresponding to the asymmetric pattern being different based on theorientation of the seatbelt; and determining a twist in the seatbeltbased on one or more changes in the orientation of the seatbelt along alength thereof.
 8. The method of claim 1, further comprising calculatingan angle of the seatbelt using detections of the seatbelt in at leasttwo different regions of interest.
 9. The method of claim 8, furthercomprising calculating a distance to the seatbelt using a pixel width ofthe seatbelt in each of the two different regions of interest.
 10. Themethod of claim 9, wherein calculating the distance to the seatbeltfurther comprises: calculating a sine of the angle of the seatbelt;multiplying a pixel width of the seatbelt by the sine of the angle ofthe seatbelt to determine a compensated pixel width; and calculating thedistance to the seatbelt based on the compensated pixel width and aknown interior width of the seatbelt.
 11. The method of claim 10,wherein the stripes of the seatbelt include a plurality of interiorstripes surrounded by outermost stripes on each of two edges along thelength of the seatbelt; and wherein the known interior width of theseatbelt is a total of the widths of the plurality of interior stripes.12. The method of claim 1, further comprising: determining if theseatbelt is properly positioned using at least one of an angle of theseatbelt or a distance to the seatbelt; and generating a signal inresponse to determining that the seatbelt is properly positioned or inresponse to determining that the seatbelt is not properly positioned.13. A system for detecting seatbelt positioning, comprising: a seatbelthaving a plurality of stripes extending lengthwise along a lengththereof, the plurality of stripes being arranged in an alternatingpattern of bright and dark in near-infrared; a camera configured tocapture a near infrared (NIR) image of an occupant wearing the seatbelt;a processor in communication with the camera and programmed to receivethe NIR image of the occupant wearing the seatbelt and to determine aposition of the seatbelt based on detecting transitions corresponding tothe alternating pattern of the stripes.
 14. The system of claim 13,wherein the processor is further programmed to convert the NIR image toa black-and-white image using a localized binary threshold to determinewhether a given pixel in the black-and-white image should be black orwhite based on whether a corresponding source pixel within the NIR imageis brighter than an average of nearby pixels within a predetermineddistance of the corresponding source pixel.
 15. The system of claim 14,wherein the predetermined distance is about 100 pixels or wherein thepredetermined distance is approximately equal to a pixel width of theseatbelt.
 16. The system of claim 13, wherein determining the positionof the seatbelt based on detecting the transitions corresponding to thealternating pattern of the stripes further comprises comparing relativedistances between the transitions to a ratio of widths of the pluralityof stripes.
 17. The system of claim 13, wherein the widths of thestripes define an asymmetric pattern.
 18. The system of claim 13,wherein the processor is further programmed to calculate a distance tothe seatbelt using a pixel width of the seatbelt and an angle of theseatbelt based upon detections of the seatbelt in each of two differentregions of interest within the NIR image.
 19. The system of claim 18,wherein calculating the distance to the seatbelt comprises furthercomprises the processor being programmed to: calculate a sine of theangle of the seatbelt; multiply a pixel width of the seatbelt by thesine of the angle of the seatbelt to determine a compensated pixelwidth; and calculate the distance to the seatbelt based on thecompensated pixel width and a known interior width of the seatbelt. 20.The system of claim 13, wherein the processor is further programmed to:determine if the seatbelt is properly positioned using at least one ofan angle of the seatbelt or a distance to the seatbelt; and generate asignal in response to determining that the seatbelt is properlypositioned or in response to determining that the seatbelt is notproperly positioned.